Sentiment Analysis of Comments on LHL's Facebook post at https://www.facebook.com/leehsienloong/posts/1505690826160285. Source: https://medium.com/google-cloud/sentiment-analysis-of-comments-on-lhls-facebook-page-9db8b3a60eb3

analyse-comments.py

import signal
import sys

from google.cloud import language
from google.api_core.exceptions import InvalidArgument

# create a Google Cloud Natural Languague API Python client
client = language.LanguageServiceClient()


# a function which takes a block of text and returns its sentiment and magnitude
def detect_sentiment(text):
    """Detects sentiment in the text."""

    document = language.types.Document(
        content=text,
        type=language.enums.Document.Type.PLAIN_TEXT)

    sentiment = client.analyze_sentiment(document).document_sentiment

    return sentiment.score, sentiment.magnitude


# keep track of count of total comments and comments with each sentiment
count = 0
positive_count = 0
neutral_count = 0
negative_count = 0


def print_summary():
    print()
    print('Total comments analysed: {}'.format(count))
    print('Positive : {} ({:.2%})'.format(positive_count, positive_count / count))
    print('Negative : {} ({:.2%})'.format(negative_count, negative_count / count))
    print('Neutral  : {} ({:.2%})'.format(neutral_count, neutral_count / count))


# register a signal handler so that we can exit early
def signal_handler(signal, frame):
    print('KeyboardInterrupt')
    print_summary()
    sys.exit(0)


signal.signal(signal.SIGINT, signal_handler)

# read our comments.txt file
with open('comments.txt', encoding='utf-8') as f:
    for line in f:
        # use a try-except block since we occasionally get language not supported errors
        try:
            score, mag = detect_sentiment(line)
        except InvalidArgument as e:
            # skip the comment if we get an error
            print('Skipped 1 comment: ', e.message)
            continue

        # increment the total count
        count += 1

        # depending on whether the sentiment is positve, negative or neutral, increment the corresponding count
        if score > 0:
            positive_count += 1
        elif score < 0:
            negative_count += 1
        else:
            neutral_count += 1

        # calculate the proportion of comments with each sentiment
        positive_proportion = positive_count / count
        neutral_proportion = neutral_count / count
        negative_proportion = negative_count / count

        print(
            'Count: {}, Positive: {:.3f}, Neutral: {:.3f}, Negative: {:.3f}'.format(
                count, positive_proportion, neutral_proportion, negative_proportion))

print_summary()

download-comments.py

import requests
import signal
import sys

graph_api_version = 'v2.9'
access_token = 'YOUR_FACEBOOK_ACCESS_TOKEN_HERE'

# LHL's Facebook user id
user_id = '125845680811480'

# the id of LHL's response post at https://www.facebook.com/leehsienloong/posts/1505690826160285
post_id = '1505690826160285'

# the graph API endpoint for comments on LHL's post
url = 'https://graph.facebook.com/{}/{}_{}/comments'.format(graph_api_version, user_id, post_id)

comments = []

# set limit to 0 to try to download all comments
limit = 200


def write_comments_to_file(filename):
    print()

    if len(comments) == 0:
        print('No comments to write.')
        return

    with open(filename, 'w', encoding='utf-8') as f:
        for comment in comments:
            f.write(comment + '\n')

    print('Wrote {} comments to {}'.format(len(comments), filename))


# register a signal handler so that we can exit early
def signal_handler(signal, frame):
    print('KeyboardInterrupt')
    write_comments_to_file('comments.txt')
    sys.exit(0)


signal.signal(signal.SIGINT, signal_handler)

r = requests.get(url, params={'access_token': access_token})
while True:
    data = r.json()

    # catch errors returned by the Graph API
    if 'error' in data:
        raise Exception(data['error']['message'])

    # append the text of each comment into the comments list
    for comment in data['data']:
        # remove line breaks in each comment
        text = comment['message'].replace('\n', ' ')
        comments.append(text)

    print('Got {} comments, total: {}'.format(len(data['data']), len(comments)))

    # check if we have enough comments
    if 0 < limit <= len(comments):
        break

    # check if there are more comments
    if 'paging' in data and 'next' in data['paging']:
        r = requests.get(data['paging']['next'])
    else:
        break

# save the comments to a file
write_comments_to_file('comments.txt')